bm sin scrap

library(RSelenium)
library(tidyverse)
library(lubridate)
library(rvest)
library(glue)
library(dplyr) #Para calcular la variación mensual
library(jsonlite)
library(plotly)
library(readxl)

link = "https://thedocs.worldbank.org/en/doc/5d903e848db1d1b83e0ec8f744e55570-0350012021/related/CMO-Historical-Data-Monthly.xlsx"


BM <- read_excel("./CMO-Historical-Data-Monthly.xlsx", sheet = "Monthly Prices", skip = 4, col_names = F)
BM_header <- BM[c(1,2), ]
BM_header <- rbind(BM_header, row3 = apply(BM_header, 2, paste0, collapse = " "))

BM_DF <- rbind(BM_header[-c(1:2),], BM[-c(1:3),])

  
names(BM_DF) <- as.matrix(BM_DF[1, ])
BM_DF <- BM_DF[-1, ]
BM_DF[] <- lapply(BM_DF, function(x) type.convert(as.character(x)))
  
colnames(BM_DF)[1] <- 'Fecha'

BM_DF$Fecha <- str_replace(BM_DF$Fecha, "M", "-")
BM_DF$Fecha <- lapply(BM_DF$Fecha, function(mes) paste(mes, "01", sep = "-")) %>%
  unlist %>%
  as.Date()